Use RStudio to fit a simple linear regression model to the data below. Please submit a copy of your code and any appropriate output (a photo/screenshot will be sufficient). 300? Is the fitted linear regression model What is the 95% prediction interval for xo = appropriate for this data, and which assumption appears to be violated if not?

The accompanying data are the caloric contents and the sugar contents​ (in grams) of 11 ​high-fiber breakfast cereals. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given​ x-values, if meaningful. If the x-value is not meaningful to predict the value of​ y, explain why not.  Calories, x         Sugar, y 140                      6 200                     10 160                      6 160                      9 170                     10 180                     16 190                     13 210                     18 190                     19 170                     10 170                     10   The equation of the regression line is ŷ =  ______ x + ______ ​(Round the slope to three decimal places as needed. Round the​ y-intercept to two decimal places as​ needed.)      (a) x = 150 cal,  ​ (b) x = 90 cal,   (c) x = 175 cal,   ​(d) x = 208 cal…

Researchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child ( height), height of the mother ( mothersheight ), and height of the father (fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS 208.008457 314.295372 522.303829 df 2 104.004228 8.49446952 37 MS 39 13.3924059 Coef. Std. Err. .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 t P>|t| 4.46 0.000 C 0.156 0.79 0.434 Number of obs = F( 2, 37) = Prob > F R-squared Adj R-squared = Root MSE = = .3591375 -.0797093 -15.32021 = 40 12.24 0.0001 0.3983 0.3657 2.9145 [95% Conf. Interval] .9567683 .4804261 34.92886 What are the null and alternative hypotheses…

The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins Click the icon to view the table of numbers of wins and earned run average. (b) x = 10 wins (c) x = 21 wins (d) x = 15 wins ERA 6- ERA 6- AERA 6- ERA 6- 4- 4- 4- 4- 2- 2- 2- 2- 0+ 6 0- 0- 0- 12 18 24 6. 12 18 24 12 18 24 6 12 18 24 Wins Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct choice below and, if necessary, fill in the answer box within your choice. A. ŷ= (Round to two decimal places as needed.) B. It is not meaningful to predict this value of y because…

I need help with finding test statistic, thanks

Pls help ASAP. Pls show all work.

The data show the bug chirps per minute at different temperatures. Find the regression​ equation, letting the first variable be the independent​ (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted​ value?   Chirps in 1 min 784 838 822 949 1188 813   Temperature ​(°​F) 65.7 67.8 66.2 79.9 92.3 73.5   What is the regression​ equation?   What is the best-predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per​ minute?   The best predicted temperature when a bug is chirping at 3000chirps per minute are?   What is wrong with this predicted​ value? Choose the correct answer below.     A. It is unrealistically high. The value 3000 is far outside of the range of observed values.   B. The first variable should have been the dependent variable.   C. It is only an…

• When fitting a linear regression, multiple regression lines may be equally as good to represent the data. True O False

Researchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child (height ), height of the mother ( mothersheight), and height of the father (fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS df 208.008457 314.295372 37 2 104.004228 8.49446952 MS 522.303829 39 13.3924059 Coef. Std. Err. .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 t P>|t| 4.46 0.000 C 0.156 0.79 0.434 Number of obs = F( 2, 37) = Prob > F R-squared Adj R-squared Root MSE = .3591375 -.0797093 -15.32021 = 40 12.24 0.0001 0.3983 0.3657 2.9145 [95% Conf. Interval] .9567683 .4804261 34.92886 What is the predicted height for a child born to a mother…

The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 760 1119 1125 850 965 785 D Temperature (°F) 70.5 90.8 90.8 74.7 77.1 69.9 What is the regression equation? (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.)